Jacob O. Wobbrock
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| title | conference | date |
|---|---|---|
| SlideAudit: A Dataset and Taxonomy for Automated Evaluation of Presentation Slides | UIST 2025 | 2025-09-28 |
Dataset of 2,400 slides and a 27 flaw types taxonomy across five categories, created with designers and annotated via trained Prolific workers (three… | ||
| Touchscreens in Motion: Quantifying the Impact of Cognitive Load on Distracted Drivers | UIST 2025 | 2025-09-28 |
Study uses N‑back to induce four cognitive loads, a Fitts’ ring task on a driving simulator, pupil and skin conductance, hand‑tracking and gaze to measure real… | ||
| An Aligned Rank Transform Procedure for Multifactor Contrast Tests | UIST 2021 | 2021-10-10 |
Introduces ART-C a new aligned-rank-contrast algorithm that claims to let aligned rank transform handle post-hoc contrasts across multiple factors without… | ||
| Type, Then Correct: Intelligent Text Correction Techniques for Mobile Text Entry Using Neural ... | UIST 2019 | 2019-10-20 |
Three mobile correction interactions are built and measured: Drag-n-Drop, Drag-n-Throw, and Magic Key. A recurrent neural network runs on a server (trained on… | ||
| Crowdsourcing Similarity Judgments for Agreement Analysis in End-User Elicitation Studies | UIST 2018 | 2018-10-14 |
A crowd-powered web tool called Crowdsensus crowdsources pairwise similarity votes and runs five unsupervised clustering algorithms to group symbols from… | ||
| Drunk User Interfaces: Determining Blood Alcohol Level through Everyday Smartphone Tasks | CHI 2018 | 2018-04-21 |
A smartphone system called the DUI app implements five tasks (typing, swiping a 3x3 passcode, PPG heart-rate hold, simple and choice reaction task) plus… | ||
| Group Touch: Distinguishing Tabletop Users in Group Settings via Statistical Modeling of Touch Pairs | CHI 2017 | 2017-05-06 |
Uses only built‑in FTIR touch data from Microsoft PixelSense, modeling distance, orientation, time between touch pairs with an MLP and a greedy grouping… | ||
| Smart Touch: Improving Touch Accuracy for People with Motor Impairments with Template Matching | CHI 2016 | 2016-05-07 |
Empirical study of 10 participants on a Microsoft PixelSense tabletop records multi-point contacts (some users produce 5–8 concurrent touches and land/lift… | ||
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